{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Equivariant Filter Bias\n",
    "\n",
    "Implementing the example in the \"Overcoming Bias\" paper by {cite:t}`https://doi.org/10.1109/LRA.2022.3210867` ([arxiv version](https://arxiv.org/pdf/2209.12038)).\n",
    "This notebook was created by converting [Alessandro Fornasier's equivariant filter code](https://github.com/aau-cns/ABC-EqF) to use GTSAM's built-in data structures.\n",
    "\n",
    "Authors: Jennifer Oum & Darshan Rajasekaran"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"https://colab.research.google.com/github/borglab/gtsam/blob/develop/python/gtsam/examples/EqF.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "remove-cell"
    ]
   },
   "source": [
    "GTSAM Copyright 2010-2022, Georgia Tech Research Corporation,\n",
    "Atlanta, Georgia 30332-0415\n",
    "All Rights Reserved\n",
    "\n",
    "Authors: Frank Dellaert, et al. (see THANKS for the full author list)\n",
    "\n",
    "See LICENSE for the license information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "remove-cell"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "# We start by installing gtsam (GTSAM's python wrapper) and gtbook.\n",
    "%pip install --quiet gtsam gtbook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import progressbar\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "\n",
    "import gtsam\n",
    "from gtsam import findExampleDataFile, Rot3\n",
    "\n",
    "from EqF import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "def formatCSV(df): # pass the dataframe in to this function and get \"data_list\" as an output\n",
    "    \"\"\"Read data from csv file formatted as follows:\n",
    "\n",
    "    | -------------------------------------------------------------------------------------------- |\n",
    "    | t: time                                                                                      |\n",
    "    | -------------------------------------------------------------------------------------------- |\n",
    "    | q_x, q_y, q_z, q_w: Quaternion representing the attitude                                     |\n",
    "    | -------------------------------------------------------------------------------------------- |\n",
    "    | b_x, b_y, b_z: Gyro bias                                                                     |\n",
    "    | -------------------------------------------------------------------------------------------- |\n",
    "    | cq_x_0, cq_yv, cq_z_0, cq_w_0: Quaternion representing the first calibration                 |\n",
    "    | ...                                                                                          |\n",
    "    | cq_x_n, cq_y_n, cq_z_n, cq_w_n: Quaternion representing the last calibration                 |\n",
    "    | -------------------------------------------------------------------------------------------- |\n",
    "    | w_x, w_y, w_z: Gyro measurements                                                             |\n",
    "    | -------------------------------------------------------------------------------------------- |\n",
    "    | std_w_x, std_w_x, std_w_z: Gyro measurements noise standard deviation                        |\n",
    "    | -------------------------------------------------------------------------------------------- |\n",
    "    | std_b_x, std_b_x, std_b_z: Gyro bias random walk standard deviation                          |\n",
    "    | -------------------------------------------------------------------------------------------- |\n",
    "    | y_x_0, y_y_0, y_z_0: Direction measurement in sensor frame associated to calibration state 0 |\n",
    "    | ...                                                                                          |\n",
    "    | y_x_n, y_y_n, y_z_n: Direction measurement in sensor frame associated to calibration state n |\n",
    "    | y_x_n+1, y_y_n+1, y_z_n+1: Direction measurement in sensor frame from calibrated sensor      |\n",
    "    | ...                                                                                          |\n",
    "    | y_x_m, y_y_m, y_z_m: Direction measurement in sensor frame from calibrated sensor            |\n",
    "    | -------------------------------------------------------------------------------------------- |\n",
    "    | std_y_x_0, std_y_y_0, std_y_z_0: Standard deviation of direction measurement y_0             |\n",
    "    | ...                                                                                          |\n",
    "    | std_y_x_m, std_y_y_m, std_y_z_m: Standard deviation of direction measurement y_m             |\n",
    "    | -------------------------------------------------------------------------------------------- |\n",
    "    | d_x_0, d_y_0, d_z_0: Known direction in global frame associated to direction measurement 0   |\n",
    "    | ...                                                                                          |\n",
    "    | d_x_m, d_y_m, d_z_m: Known direction in global frame associated to direction measurement m   |\n",
    "    | -------------------------------------------------------------------------------------------- |\n",
    "\n",
    "    NaN cell means that value is not present at that time\n",
    "\n",
    "    Max allowd n = 5\n",
    "    Max allowd m = 10\n",
    "\n",
    "    :param pname: path name\n",
    "    \"\"\"\n",
    "\n",
    "    # read .csv file into pandas dataframe\n",
    "    df = df.reset_index()\n",
    "\n",
    "    # Define data_list as list\n",
    "    data_list = []\n",
    "    last_timestamp = df.t[0]\n",
    "\n",
    "    # Check for existence of bias ground-truth into loaded data\n",
    "    bias_exist = False\n",
    "    if {'b_x', 'b_y', 'b_z'}.issubset(df.columns):\n",
    "        bias_exist = True\n",
    "\n",
    "    # Check for existence of calibration ground-truth (yaw, pitch, roll angles) into loaded data\n",
    "    cal_exist = False\n",
    "    n_cal = 0\n",
    "    for i in range(6):\n",
    "        if {'cq_x_' + str(i), 'cq_y_' + str(i), 'cq_z_' + str(i), 'cq_w_' + str(i)}.issubset(df.columns):\n",
    "            cal_exist = True\n",
    "            n_cal = i+1\n",
    "\n",
    "    # Check for existence of direction measurements\n",
    "    n_meas = 0\n",
    "    for i in range(11):\n",
    "        if {'y_x_' + str(i), 'y_y_' + str(i), 'y_z_' + str(i)}.issubset(df.columns):\n",
    "            n_meas = i + 1\n",
    "\n",
    "    for index, row in df.iterrows():\n",
    "\n",
    "        # Load timestamps and record dt\n",
    "        t = float(row['t'])\n",
    "        dt = t - last_timestamp\n",
    "\n",
    "        # Skip data_list if dt is smaller than a micro second\n",
    "        if dt < 1e-6:\n",
    "            continue\n",
    "\n",
    "        last_timestamp = t\n",
    "\n",
    "        # Load groundtruth values\n",
    "        quat = np.array([float(row['q_x']), float(row['q_y']), float(row['q_z']), float(row['q_w'])])\n",
    "\n",
    "        R = Rot3(gtsam.Rot3.Quaternion(float(row['q_w']), float(row['q_x']), float(row['q_y']), float(row['q_z'])).matrix())\n",
    "\n",
    "        # Load Gyro biases\n",
    "        if bias_exist:\n",
    "            b = np.array([float(row['b_x']), float(row['b_y']), float(row['b_z'])]).reshape(3,)\n",
    "        else:\n",
    "            b = np.zeros(3)\n",
    "\n",
    "        # Load GNSS calibration\n",
    "        S = []\n",
    "        if cal_exist:\n",
    "            for i in range(n_cal):\n",
    "                cal = np.array([float(row['cq_x_' + str(i)]), float(row['cq_y_' + str(i)]), float(row['cq_z_' + str(i)]), float(row['cq_w_' + str(i)])])\n",
    "                S.append(Rot3(gtsam.Rot3.Quaternion(float(row['cq_w_' + str(i)]), float(row['cq_x_' + str(i)]), float(row['cq_y_' + str(i)]), float(row['cq_z_' + str(i)])).matrix()))\n",
    "\n",
    "\n",
    "        # Load Gyro inputs\n",
    "        w = np.array([float(row['w_x']), float(row['w_y']), float(row['w_z'])]).reshape(3,)\n",
    "        std_w = np.array([float(row['std_w_x']), float(row['std_w_y']), float(row['std_w_z'])]).reshape(3,)\n",
    "        std_b = np.array([float(row['std_b_x']), float(row['std_b_y']), float(row['std_b_z'])]).reshape(3,)\n",
    "        Sigma_wb = blockDiag(np.eye(3) * (std_w ** 2), np.eye(3) * (std_b ** 2))\n",
    "\n",
    "        # Load measurements\n",
    "        meas = []\n",
    "        for i in range(n_meas):\n",
    "            y = np.array([float(row['y_x_' + str(i)]), float(row['y_y_' + str(i)]), float(row['y_z_' + str(i)])]).reshape(3,)\n",
    "            d = np.array([float(row['d_x_' + str(i)]), float(row['d_y_' + str(i)]), float(row['d_z_' + str(i)])]).reshape(3,)\n",
    "            std_y = np.array([float(row['std_y_x_' + str(i)]), float(row['std_y_y_' + str(i)]), float(row['std_y_z_' + str(i)])]).reshape(3,)\n",
    "            if i < n_cal:\n",
    "                meas.append(Measurement(y, d, np.eye(3) * (std_y ** 2), i))\n",
    "            else:\n",
    "                meas.append(Measurement(y, d, np.eye(3) * (std_y ** 2), -1))\n",
    "\n",
    "        # Append to data_list\n",
    "        d = Data(State(R, b, S), n_cal, Input(w, Sigma_wb), meas, n_meas, t, dt)\n",
    "        \n",
    "        data_list.append(d)\n",
    "\n",
    "    return data_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sim(filter_args, data):\n",
    "\n",
    "    # Define progressbar\n",
    "    p = progressbar.ProgressBar()\n",
    "\n",
    "    # EqF\n",
    "    filter = EqF(*filter_args)\n",
    "\n",
    "    # Allocate variables\n",
    "    t = []\n",
    "    est = []\n",
    "\n",
    "    # Filter loop\n",
    "    for d in p(data):\n",
    "\n",
    "        t.append(d.t)\n",
    "\n",
    "        # Run filter\n",
    "        try:\n",
    "            filter.propagation(d.u, d.dt)\n",
    "        except:\n",
    "            print('Filter.propagation Error\\n')\n",
    "        for y in d.y:\n",
    "            if not (np.isnan(np.linalg.norm(y.y.d.unitVector())) or np.isnan(np.linalg.norm(y.d.d.unitVector()))):\n",
    "                try:\n",
    "                    filter.update(y)\n",
    "                except:\n",
    "                    print('Filter.update Error\\n')\n",
    "        est.append(filter.stateEstimate())\n",
    "\n",
    "    # Plot Attitude1\n",
    "    fig, (ax0, ax1, ax2) = plt.subplots(3, 1)\n",
    "    ax = [ax0, ax1, ax2]\n",
    "    for i in range(3):\n",
    "        ax[i].plot(t, [d.xi.R.rpy()[i] * 180 / math.pi for d in data], color=\"C0\")\n",
    "        ax[i].plot(t, [xi.R.rpy()[i] * 180 / math.pi for xi in est], color=\"C1\")\n",
    "        ax[i].set_xlabel(\"t\")\n",
    "    ax0.set_title(\"Attitude: Roll\")\n",
    "    ax1.set_title(\"Attitude: Pitch\")\n",
    "    ax2.set_title(\"Attitude: Yaw\")\n",
    "    plt.show()\n",
    "\n",
    "    # Plot bias\n",
    "    fig, (ax0, ax1, ax2) = plt.subplots(3, 1)\n",
    "    ax = [ax0, ax1, ax2]\n",
    "    for i in range(3):\n",
    "        ax[i].plot(t, [d.xi.b[i] for d in data], color=\"C0\")\n",
    "        ax[i].plot(t, [xi.b[i] for xi in est], color=\"C1\")\n",
    "        ax[i].set_xlabel(\"t\")\n",
    "    ax0.set_title(\"Bias: x\")\n",
    "    ax1.set_title(\"Bias: y\")\n",
    "    ax2.set_title(\"Bias: z\")\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "    # Plot calibration states\n",
    "    for j in range(data[0].n_cal):\n",
    "        fig, (ax0, ax1, ax2) = plt.subplots(3, 1)\n",
    "        ax = [ax0, ax1, ax2]\n",
    "        for i in range(3):\n",
    "            ax[i].plot(t, [d.xi.S[j].rpy()[i] * 180 / math.pi for d in data], color=\"C0\")\n",
    "            ax[i].plot(t, [xi.S[j].rpy()[i] * 180 / math.pi for xi in est], color=\"C1\")\n",
    "            ax[i].set_xlabel(\"t\")\n",
    "        ax0.set_title(\"Calibration: Roll\")\n",
    "        ax1.set_title(\"Calibration: Pitch\")\n",
    "        ax2.set_title(\"Calibration: Yaw\")\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run Equivariant Filter\n",
    "\n",
    "(1) Load gyroscope and direction measurement data from EqFdata.csv. See formatCSV function for detailed description.\n",
    "\n",
    "(2) Initialize the covariance, Sigma.\n",
    "\n",
    "(3) Run the equivariant filter by passing in Sigma, number of calibration states, total number of available sensors, and the csv data to the sim function.\n",
    "\n",
    "(4) Outputs 3 plots comparing the truth data (blue line) to the filter estimate (orange line.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading dataset:\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100% |########################################################################|\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Seed\n",
    "np.random.seed(0)\n",
    "\n",
    "# Load dataset\n",
    "print(f\"Loading dataset:\\n\")\n",
    "df = pd.read_csv(findExampleDataFile(\"EqFdata.csv\"))\n",
    "data = formatCSV(df) \n",
    "\n",
    "# Define initial covariance\n",
    "Score = blockDiag(np.eye(3), 0.1 * np.eye(3))\n",
    "Scal = repBlock(np.eye(3), data[0].n_cal)\n",
    "Sigma = blockDiag(Score, Scal)\n",
    "\n",
    "# Run filter\n",
    "filter_args = [Sigma, data[0].n_cal, data[0].n_meas]\n",
    "sim(filter_args, data)\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
